rp function

Random samples from the prior of a hyper2 object

Uses Metropolis-Hastings to return random samples from the prior of a hyper2 object

rp(n, H, startp = NULL, fcm = NULL, fcv = NULL, SMALL = 1e-06, l=loglik, fillup=TRUE, ...)

Arguments

• H: Object of class hyper2
• n: Number of samples
• startp: Starting value for the Markov chain, with default NULL being interpreted as starting from the evaluate
• fcm,fcv: Constraints as for maxp()
• SMALL: Notional small value for numerical stability
• l: Log-likelihood function with default loglik()
• fillup: Boolean, with default TRUE meaning to return a matrix with the fillup value added, and column names matching the pnames() of argument H
• ...: Further arguments, currently ignored

Details

Uses the implementation of Metropolis-Hastings from the MCE

package to sample from the posterior PDF of a hyper2 object.

If the distribution is Dirichlet, use rdirichlet() to generate random observations: it is much faster, and produces serially independent samples. To return uniform samples, use rp_unif() (documented at dirichlet.Rd).

Returns

Returns a matrix, each row being a unit-sum observation.

Author(s)

Robin K. S. Hankin

Note

Function rp() a random sample from a given normalized likelihood function. To return a random likelihood function, use rhyper2().

File inst/ternaryplot_hyper2.Rmd shows how to use Ternary::ternaryPlot() with rp().

See Also

maxp,loglik,dirichlet,rhyper2

Examples

rp(10,icons)

plot(loglik(rp(30,icons),icons),type='b')